Civil and Environmental Engineering Challenges for Data Sensing and Analysis

The objective of this study was to identify challenges in civil and environmental engineering that can potentially be solved using data sensing and analysis research. The challenges were recognized through extensive literature review in all disciplines of civil and environmental engineering. The literature review included journal articles, reports, expert interviews, and magazine articles. The challenges were ranked by comparing their impact on cost, time, quality, environment and safety. The result of this literature review includes challenges such as improving construction safety and productivity, improving roof safety, reducing building energy consumption, solving traffic congestion, managing groundwater, mapping and monitoring the underground, estimating sea conditions, and solving soil erosion problems. These challenges suggest areas where researchers can apply data sensing and analysis research.

Automated 3D Structure Inference of Civil Infrastructure Using a Stereo Camera Set

The commercial far-range (>10m) infrastructure spatial data collection methods are not completely automated. They need significant amount of manual post-processing work and in some cases, the equipment costs are significant. This paper presents a method that is the first step of a stereo videogrammetric framework and holds the promise to address these issues. Under this method, video streams are initially collected from a calibrated set of two video cameras. For each pair of simultaneous video frames, visual feature points are detected and their spatial coordinates are then computed. The result, in the form of a sparse 3D point cloud, is the basis for the next steps in the framework (i.e., camera motion estimation and dense 3D reconstruction). A set of data, collected from an ongoing infrastructure project, is used to show the merits of the method. Comparison with existing tools is also shown, to indicate the performance differences of the proposed method in the level of automation and the accuracy of results.

Generating the Sparse Point Cloud of a Civil Infrastructure Scene Using a Single Video Camera under Practical Constraints

Automating the model generation process of infrastructure can substantially reduce the modeling time and cost. This paper presents a method to generate a sparse point cloud of an infrastructure scene using a single video camera under practical constraints. It is the first step towards establishing an automatic framework for object-oriented as-built modeling. Motion blur and key frame selection criteria are considered. Structure from motion and bundle adjustment are explored. The method is demonstrated in a case study where the scene of a reinforced concrete bridge is videotaped, reconstructed, and metrically validated. The result indicates the applicability, efficiency, and accuracy of the proposed method.

Optimized selection of key frames for monocular videogrammetric surveying of civil infrastructure

Videogrammetry is an inexpensive and easy-to-use technology for spatial 3D scene recovery. When applied to large scale civil infrastructure scenes, only a small percentage of the collected video frames are required to achieve robust results. However, choosing the right frames requires careful consideration. Videotaping a built infrastructure scene results in large video files filled with blurry, noisy, or redundant frames. This is due to frame rate to camera speed ratios that are often higher than necessary; camera and lens imperfections and limitations that result in imaging noise; and occasional jerky motions of the camera that result in motion blur; all of which can significantly affect the performance of the videogrammetric pipeline. To tackle these issues, this paper proposes a novel method for automating the selection of an optimized number of informative, high quality frames. According to this method, as the first step, blurred frames are removed using the thresholds determined based on a minimum level of frame quality required to obtain robust results. Then, an optimum number of key frames are selected from the remaining frames using the selection criteria devised by the authors. Experimental results show that the proposed method outperforms existing methods in terms of improved 3D reconstruction results, while maintaining the optimum number of extracted frames needed to generate high quality 3D point clouds.© 2012 Elsevier Ltd. All rights reserved.

Achievements and Challenges in Recognizing and Reconstructing Civil Infrastructure

The US National Academy of Engineering recently identified restoring and improving urban infrastructure as one of the grand challenges of engineering. Part of this challenge stems from the lack of viable methods to map/label existing infrastructure. For computer vision, this challenge becomes “How can we automate the process of extracting geometric, object oriented models of infrastructure from visual data?” Object recognition and reconstruction methods have been successfully devised and/or adapted to answer this question for small or linear objects (e.g. columns). However, many infrastructure objects are large and/or planar without significant and distinctive features, such as walls, floor slabs, and bridge decks. How can we recognize and reconstruct them in a 3D model? In this paper, strategies for infrastructure object recognition and reconstruction are presented, to set the stage for posing the question above and discuss future research in featureless, large/planar object recognition and modeling.

Spin-cluster effect and lattice-deformation-induced Kondo effect, spin-glass freezing, and strong phonon scattering in La 0.7 Ca 0.3Mn 1-xCr xO 3

Besides the Kondo effect observed in dilute magnetic alloys, the Cr-doped perovskite manganate compounds La0.7 Ca0.3 Mn1-x Crx O3 also exhibit Kondo effect and spin-glass freezing in a certain composition range. An extensive investigation for the La0.7 Ca0.3 Mn1-x Crx O3 (x=0.01, 0.05, 0.10, 0.3, 0.6, and 1.0) system on the magnetization and ac susceptibility, the resistivity and magnetoresistance, as well as the thermal conductivity is done at low temperature. The spin-glass behavior has been confirmed for these compounds with x=0.05, 0.1, and 0.3. For temperatures above Tf (the spin-glass freezing temperature) a Curie-Weiss law is obeyed. The paramagnetic Curie temperature θ is dependent on Cr doping. Below Tf there exists a Kondo minimum in the resistivity. Colossal magnetoresistance has been observed in this system with Cr concentration up to x=0.6. We suppose that the substitution of Mn with Cr dilutes Mn ions and changes the long-range ferromagnetic order of La0.7 Ca0.3 MnO3. These behaviors demonstrate that short-range ferromagnetic correlation and fluctuation exist among Mn spins far above Tf. Furthermore, these interactions are a precursor of the cooperative freezing at Tf. The "double bumps" feature in the resistivity-temperature curve is observed in compounds with x=0.05 and 0.1. The phonon scattering is enhanced at low temperatures, where the second peak of double bumps comes out. The results indicate that the spin-cluster effect and lattice deformation induce Kondo effect, spin-glass freezing, and strong phonon scattering in mixed perovskite La0.7 Ca0.3 Mn1-x Crx O3. © 2005 American Institute of Physics.

Spin glass behaviour and spin-dependent scattering in la 0.7Ca 0.3Mn 0.9Cr 0.1O 3 perovskites

The magnetic, electrical and thermal transport properties of the perovskite La 0.7Ca 0.3Mn 0.9Cr 0.1O 3 have been investigated by measuring dc magnetization, ac susceptibility, the magnetoresistance and thermal conductivity in the temperature range of 5-300K. The spin glass behaviour with a spin freezing temperature of 70 K has been well confirmed for this compound, which demonstrates the coexistence and competition between ferromagnetic and antiferromagnetic clusters by the introduction of Cr. Colossal magnetoresistance has been observed over the temperature range investigated. The introduction of Cr causes the "double-bump" feature in electrical resistivity ρ(T). Anomalies on the susceptibility and the thermal conductivity associated with the double-bumps in ρ(T) are observed simultaneously. The imaginary part of ac susceptibility shows a sharp peak at the temperature of insulating-metallic transition where the first resistivity bump was observed, but it is a deep-set valley near the temperature where the second bump in ρ(T) emerges. The thermal conductivity shows an increase below the temperature of the insulating-metallic transition, but the phonon scattering is enhanced accompanying the appearance of the second peak of double-bumps in ρ(T). We relate those observed in magnetic and transport properties of La 0.7Ca 0.3Mn 0.9Cr 0.1O 3 to the spin-dependent scattering. The results reveal that the spin-phonon interaction may be of more significance than the electron (charge)-phonon interaction in the mixed perovskite system. © 2005 Chinese Physical Society and IOP Publishing Ltd.

Global civil aviation black carbon emissions.

Aircraft black carbon (BC) emissions contribute to climate forcing, but few estimates of BC emitted by aircraft at cruise exist. For the majority of aircraft engines the only BC-related measurement available is smoke number (SN)-a filter based optical method designed to measure near-ground plume visibility, not mass. While the first order approximation (FOA3) technique has been developed to estimate BC mass emissions normalized by fuel burn [EI(BC)] from SN, it is shown that it underestimates EI(BC) by >90% in 35% of directly measured cases (R(2) = -0.10). As there are no plans to measure BC emissions from all existing certified engines-which will be in service for several decades-it is necessary to estimate EI(BC) for existing aircraft on the ground and at cruise. An alternative method, called FOX, that is independent of the SN is developed to estimate BC emissions. Estimates of EI(BC) at ground level are significantly improved (R(2) = 0.68), whereas estimates at cruise are within 30% of measurements. Implementing this approach for global civil aviation estimated aircraft BC emissions are revised upward by a factor of ~3. Direct radiative forcing (RF) due to aviation BC emissions is estimated to be ~9.5 mW/m(2), equivalent to ~1/3 of the current RF due to aviation CO2 emissions.